Learning 6DoF Grasp-poses in Occluded Scenes Using RGB and 3D Point Cloud Modalities-Reference-Cited by-同舟云学术

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Learning 6DoF Grasp-poses in Occluded Scenes Using RGB and 3D Point Cloud Modalities

Published:2023-02-23 Issue: Volume: Page:
ISSN:
Container-title:2023 National Conference on Communications (NCC)
language:
Short-container-title:

Author:

Mathur Abhay Dayal¹,Bhadang Sachin¹,Raj Prem²,Behera Laxmidhar³,Sandhan Tushar⁴

Affiliation:

1. Mechanical Engineering Indian Institute of Technology,Kanpur

2. Computer Science & Engineering Indian Institute of Technology,Kanpur

3. Electrical Engineering Indian Institute of Technology,Mandi

4. Electrical Engineering Indian Institute of Technology,Kanpur

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10067865/10067872/10068034.pdf?arnumber=10068034

Reference43 articles.

1. Yolov4: Optimal speed and accuracy of object detection;bochkovskiy,2020

2. Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection

3. Deep residual learning for image recognition;he,2015

4. Apple detection during different growth stages in orchards using the improved YOLO-V3 model

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1. Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06

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